Raster-to-Graph is a novel automatic recognition framework, which achieves structural and semantic recognition of floorplans, addresses the problem of obtaining high-quality vectorized floorplans from ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

In this exclusive virtual interview with DATAQUEST, Srini Srinivasan discusses the transformative role of vector databases, the challenges of scaling AI at real-time speed, the evolving architecture ...

The way you build images is with a parent <vector-graph> that draws the image and few top-level configuration (like the axis, grid, etc) and then add elements inside. Unless specified otherwise all ...

The job shop scheduling problem (JSSP) is a classic NP-hard problem. This article focuses on a realistic variant of the JSSP incorporating fuzzy processing times, with the objective of minimizing the ...

Graph Neural Networks have demonstrated significant success in fraud detection tasks. However, most existing approaches, which rely on distinct message-passing mechanisms to aggregate node information ...